Association between autonomic control indexes and mortality in subjects admitted to intensive care unit

This study checks whether autonomic markers derived from spontaneous fluctuations of heart period (HP) and systolic arterial pressure (SAP) and from their interactions with spontaneous or mechanical respiration (R) are associated with mortality in patients admitted to intensive care unit (ICU). Three-hundred consecutive HP, SAP and R values were recorded during the first day in ICU in 123 patients. Population was divided into survivors (SURVs, n = 83) and non-survivors (NonSURVs, n = 40) according to the outcome. SURVs and NonSURVs were aged-and gender-matched. All subjects underwent modified head-up tilt (MHUT) by tilting the bed back rest segment to 60 degrees. Autonomic control indexes were computed using time-domain, spectral, cross-spectral, complexity, symbolic and causality techniques via univariate, bivariate and conditional approaches. SAP indexes derived from time-domain, model-free complexity and symbolic approaches were associated with the endpoint, while none of HP variability markers was. The association was more powerful during MHUT. Linear cross-spectral and causality indexes were useless to separate SURVs from NonSURVs, while nonlinear bivariate symbolic markers were successful. When indexes were combined with clinical scores, only SAP variance provided complementary information. Cardiovascular control variability indexes, especially when derived after an autonomic challenge such as MHUT, can improve mortality risk stratification in ICU

A Framework to Measure the Progress of Societies

Over the last three decades, a number of frameworks have been developed to promote and measure well-being, quality of life, human development and sustainable development. Some frameworks use a conceptual approach while others employ a consultative approach, and different initiatives to measure progress will require different frameworks. The aim of this paper is to present a proposed framework for measuring the progress of societies, and to compare it with other progress frameworks that are currently in use around the world. The framework does not aim to be definitive, but rather to suggest a common starting point that the authors believe is broad-based and flexible enough to be applied in many situations around the world. It is also the intention that the framework could be used to identify gaps in existing statistical standards and to guide work to fill these gaps

Design and rationale for the treating obstructive sleep apnea using targeted hypoglossal neurostimulation (OSPREY) trial

Obstructive sleep apnea (OSA) affects nearly 1 billion people worldwide, including approximately 35 million US residents. OSA has detrimental cardiovascular and neurocognitive consequences. Positive airway pressure corrects sleep disordered breathing but is not always tolerated or used sufficiently. Oral appliances and surgery provide alternatives in select populations but are variably effective. Hypoglossal nerve stimulation can effectively treat obstructive sleep apnea. Targeted hypoglossal nerve stimulation (THN) is simpler than incumbent technology with no sensor and an easier, proximal electrode implantation. The third clinical study of THN, THN3, was the first randomized, controlled trial of hypoglossal nerve stimulation to demonstrate significant improvement of sleep disordered breathing in OSA. The present investigation reports the design of a novel trial of targeted stimulation to provide additional Level 1 evidence in moderate to severe obstructive apnea. OSPREY is a randomized, parallel-arm, 13-month trial wherein all subjects are implanted, 2/3 are activated at Month 1 ("Treatment") and 1/3 are activated at Month 7 ("Control"). The primary endpoint is the difference in apnea-hypopnea index response rates between Treatment and Control groups at Month 7. Secondary endpoints include quality of life and oximetry metrics. OSPREY follows an adaptive "Goldilocks" design which optimizes the number of subjects with the need for high-confidence results. A maximum of 150 subjects is allowed, at which study power of >95% is predicted. Interim analyses begin once 50 patients are randomized and recur after each 20 additional randomizations to detect early success or futility. OSPREY is a unique, efficient trial that should provide high-confidence confirmation of the safety and efficacy of targeted hypoglossal nerve stimulation for moderate to severe obstructive sleep apnea

Stratifying the risk of developing atrial fibrillation after coronary artery bypass graft surgery using heart rate asymmetry indexes

Heart period (HP) asymmetry (HPA) is a peculiar pattern detectable over short-term HP variability recordings suggesting that cardiac deceleration runs are shorter than acceleration ones in healthy subjects. We tested the hypothesis that two traditional HPA indexes, namely the Porta's index (PI) and Guzik's index (GI), can distinguish patients scheduled for coronary artery bypass graft (CABG) surgery developing atrial fibrillation (AF) after surgery from the ones who do not (noAF). HP was derived from the electrocardiogram in 130 patients scheduled for CABG before (PRE) and after (POST) the induction of general anesthesia. PI assesses the percentage of positive HP changes, while GI quantifies the percent sum of the squared positive variations. Positive departures from 50 suggest that a series exhibits HPA. Surrogate analysis was exploited to assess the significant presence of HPA patterns. The likelihood of detecting HPA patters was higher in AF subjects and this result held during PRE. GI featured a greater statistical power than PI. Neither HP mean nor variance distinguished the two groups. HPA indexes can be exploited to improve stratification of the risk for post-surgery AF

Towards the identification of subjects prone to develop atrial fibrillation after coronary artery bypass graft surgery via univariate and multivariate complexity analysis of heart period variability

The assessment of cardiovascular control complexity as derived from spontaneous heart period (HP) fluctuations can be improved by exploiting a multivariate (MV) approach. This work proposes the assessment of a normalized complexity index (NCI) of HP variability according to a k-nearest-neighbor approach based on local predictability performed in a MV nonuniform embedding space. The method allows the selection of the past components of HP, systolic arterial pressure (SAP) and respiration (R) most useful for the prediction of HP fluctuations. The NCI derived from the MV approach (NCIMV) was compared to a NCI computed via the same technique applied in a univariate (UV) embedding space (NCIUV) formed exclusively by HP past samples. Indexes were computed in 130 patients undergoing coronary artery bypass graft (CABG) surgery before and after the induction of general anesthesia. Thirty-eight subjects developed atrial fibrillation (AF) after surgery, while the remaining ones did not (noAF, n=92). Both NCIUV and NCIMV could separate AF from noAF patients and revealed a larger complexity of the AF subjects. However, the statistical power of the NCIMV was superior given that the probability of type I error was smaller than that of NCIUV. The assessment of cardiac control complexity could improve risk stratification of patients at risk of developing AF after CABG surgery